We are very proud to share the interview Sean Copeland has conducted with Alon Ravid and Tal Sliwowicz for his New Market Research blog.

In the interview we explained how groketeer had started and what makes it such a revolutionary product. We discussed new trends in Market Research industry and shared some of our plans for the future.

Here are some quotes to intrigue you to read the full interview:

“Groketeer fills a huge hole for people who create and send out surveys themselves (DIY Surveys) but don’t have a good solution on how to analyze the collected data and create reports out of it."

“The big difference between groketeer and other tools is in its ease of use. We have designed it from the ground up with usability in mind so users are productive with groketeer from the first minute they use it.”

“Only the ones who adapt themselves to the new reality will survive – and the reality is that DIY is here to stay”

“What we are doing with groketeer is simply giving people that already use DIY surveys regardless of groketeer, a great tool to do their data analysis quickly and easily. It is a huge time saver for them and compared to the analysis tools they have been using so far – a big relief.”

Read the full interview here.

In this blog post, I want to share with you something a bit different.

We've just published groketeer's first printed ad. With this exciting event, I want to share with you some of the ad's early concepts and its final outcome.

We started the design process of the ad by stating the messages it should deliver. These messages should best describe the essence of groketeer. We came up with two main ones:

• The ad should demonstrate the magic that occurs in groketeer, as raw data comes in and insight reveals
• The ad should express how easy it is to work with groketeer

We came up with 3 concepts from which we had to choose one, a task that has turned to be more complex than we expected.

Which one would you choose?

The King

The Magician

The Miraculous Lens

And the winner is…

It was difficult to choose the best one. We wandered through corridors and rooms in our offices asking for people's opinions, but we couldn't reach a clear consensus.

Finally, 'The Miraculous Lens' ad was selected, as this one manifests best the essence of groketeer and delivers the two messages we initially states: Magical and Easy to Use.

Here is the final ad:

*We want to thank Jan Futtrup Kjaer from SocialSemantic.eu for his quote for the ad.

With the availability of online survey tools today, it has never been easier to create a survey for your friends, family and more increasingly your place of work. There is no secret the feedback can be extremely helpful for selecting food for a get-together that everyone will enjoy, improving consumer satisfaction or getting some original ideas from your customer base on a new product or service.

Although it has become increasingly easy to create a survey it is important to keep in mind that there are many seemingly innocent mistakes that can greatly reduce the validity of your results if not completely discredit them.

Last week we discussed the five simplest ways to discredit your research which included ambiguity, incomprehensible/unanswerable questions, leading questions, loaded questions and double-barreled questions. To further insure your research is credible there are additional subtleties when asking questions that one should keep in mind.

• Be Direct
• “May I know your age?”
• “What is your age?”
• Avoid fancy or slag words
• Use “like” not “appreciate”
• Use “like” not “cool”
• When rating a product, service or idea, specify, specify, specify.
• “How much do you like Apple products?”
• “How much do you like Apple products for gaming… for art?”
• Topic Bias
• Some topics are more sensitive in certain communities, cultures, countries or even industries. Know your audience!
• Ask simple questions not compound questions
• “Have you stopped eating fast food?” (one may have never started)

Designing the perfect survey is no simple task and will most likely be tedious at times but don’t be disheartened; even today students around the world are studying to receive their Undergraduate, Masters and PHD degrees in the field of market research and analytics. Keep this in mind when designing your survey and have a friend or coworker review your survey before you send it off to insure it is clear, concise and to the point.

Creating an online survey today is simple: google a free survey tool, type up the questions you would like to ask and distribute the link. In essence it is simple, but all too often simple mistakes can discredit your conclusions from the survey.

To get to really understand what your data says and to gain real and credible insight from your survey, you first have to make sure that the data itself is credible. After collecting credible data you need to analyze it correctly to get to really understand what the collected data means.

In previous blog posts we have discussed the analysis part. In this blog post, I’ll try to cover a few key points regarding data collection and specifically – how to avoid some key mistakes in phrasing your survey questions.

It is important to keep the following in mind for each and every question you create:

Ambiguous questions/answers

How often do you use your bike?

• Regularly
• Sometimes
• Occasionally
• Never

In this example no real value can be extracted from respondent’s answers as each choice is subjective. To avoid this - make sure the question incorporates a standard, be it time or usage.

How often do you use your bike?

• Use almost every day
• About once per week
• About once per month
• Never

Incomprehensible/Unanswerable questions

Incomprehensible: What is your attitude about the increase in gas prices by oil companies due to legislation passed by the government to increase the number of jobs?

Unanswerable: What was the average price you paid for a gallon of gas in October of 2009?

In both situations there may be a reason for asking the question, but if the respondent can not accurately answer, the responses will be invalid and of no use. To avoid this – use short and clear sentences, avoid double negatives and make sure that you are asking questions that can be answered during the survey without deep research.

Leading questions

The government has done nothing to protect your online privacy and your personal information is legally being sold to many large corporations to make money off of you. Do you personally believe this is a violation of your personal rights?

• Yes
• No

Leading a respondent to your “answer of choice” may be self gratifying when looking over the results or proving your hypothesis, but keep in mind this will completely discredit your results and negate the purpose of the survey in the first place. To avoid this – do not use phrases or statements that might lead the user to an answer.

Loaded questions

You care about your health, don’t you?

• Yes
• No

A loaded question carries unintended connotations. In the example above, respondents will almost always respond yes due to the negative social stigma of not taking care of oneself and that fact that everyone case about their health in one facet or another.

Double-barreled questions

What is your assessment of the price and convenience offered by Strabucks?

• Excellent
• Average
• Below Average
• Poor

In this example, two unique and different attributes in regards to Strabucks are asked in a single question. A respondent is forced to answer both attributes as one providing no distinction between the respondent’s assessment of price and convenience. For this question to be valid it would need to be separated into two distinct questions.

Next week we at the groketeer blog will look at how additional subtleties in how you ask questions will affect the credibility and integrity of your online survey data.

The second installment of Improving Survey Analysis for SurveyMonkey™, introduces groketeer and shows how it provides answers to the main questions raised in part one.

I'll explain how working with SurveyMonkey™'s data on groketeer is effortless and streamlined and how groketeer lets you really understand what the numbers are saying rather than letting the details obscure the overall picture.

The Feedback Chief

SurveyMonkey™ is a great tool to gather feedback easily, quickly and cheaply.
As we've discussed in the previous part, SurveyMonkey™ has its weaknesses when it comes to understand the feedback gathered.
Collecting feedback and understanding the data gathered are two distinct challenges, each requiring its unique expertise.

And groketeer?

Here is where groketeer comes to action.
Whenever I finish collecting responses in SurveyMonkey™ I upload the data file to groketeer. Doing it is just a matter of a few clicks and it takes me only one minute of my time.
Opening the groketeer dashboard is a joy to the eyes.
All my questions are displayed, charted with neat graphs.
Visually, the information is displayed so lucidly, that I immediately get a clear picture of what is going on. Although I'm looking at the exact same data I just saw in SurveyMonkey™, in groketeer it all looks surprisingly uncomplicated.

*groketeer (left) vs. SurveyMonkey™ (right); can you tell the difference?

A careful look will reveal that only the important information is shown. The display doesn't overwhelm you with details you rarely need, although if you do decide to drill down, you can easily get the additional information by interacting with the chart. The survey’s information is easily understandable, and while you walk through the survey's data, the picture becomes crystal clear.

Moreover, using a smart algorithm, groketeer also chooses for me the best possible display for each question. I can then further customize the display according to my preferences. As I choose another chart type for a question, the chart is shown immediately and is saved for me even if I exit the dashboard and get back to it at a later time.

Revealing Insight

groketeer’s philosophy is to let you have the data at your fingertips.
Discoveries emerge as groketeer displays data. Using the filtering capability you can break the audience down to its segments, based on answers to other questions.
Crossing question with other ones can reveal unexpected discoveries.

Take a look at the 'HOWTO video - using filters' blog post to see an interesting example on how looking at the entire sample results shows only a single aspect of the story.

*Quality of Products and Services by Usage Frequency

In that example the aggregated results, reflecting the entire sample, show high satisfaction from the product. However when the audience was broken into segments based only usage frequency, another story was revealed. Satisfaction was reduced as the frequency of usage was increasing. Leading to the unpleasant conclusion that as users use the product more often they like it less!
Inspecting the data from a single view doesn't tell and whole story and can sometimes be misleading.

Using groketeer you can cross any question with any other one, choose the appropriate chart display, run statistics, play with the data, make mistakes, correct them, so that soon you will reach a meaningful insight.

Previous: Improving Survey Analysis for SurveyMonkey™: Part 1

SurveyMonkey™ is a great service. It's cheap, it's easy to use, it has the right collection of features and most importantly, it serves a purpose. But what about the analysis of data collected with it? In many cases for real analysis you cannot use the tool itself and have to use other tools. In the next two blog posts, I’ll try to examine this issue.

About Looking Cool

Whenever I need to collect my friends' feedback about a certain issue and reach a consensus, instead of just sending an email and receiving a dozen replies, I quickly setup a short survey and publish it among them. It's easy, it's cheep and let’s face it…it makes me look cooler.
But there is a but ….

When it comes to viewing and understanding the feedback gathered, things get less cheerful and more complex.

Yes, I can see all the questions and answers in a table layout.
And Yes, I can create charts.
And yes again, I can filter and crosstab the results.

So if everything is so great, why do I have problems understanding what the data is really saying?

Wandering around SurveyMonkey™ 'Analyze Results' section made me realize that there are two main weaknesses in their offering having to do with Data Visualization and The Big Picture.

About Data Visualization

Data Visualization is a science. The ability to summarize hundreds or thousands of pieces of information into a single meaningful picture is far from trivial, and should be carefully thought out.

In SurveyMonkey™, charts do not serve as means for understanding the data; they are used merely for decoration, and are referred to as such. You can easily create charts for a question to decorate your report, but you get to see them only in a modal window, one chart at a time, outside of the survey's context. And if you want to download them you'll get only a still image, which is a dead-end for further analysis. Visualizing data outside of the survey context in not just worthless it can also be misleading.

Let’s look at an example of what happens when visualizing data in a wrong way.
Take the simple, commonly used pie chart.
The circle, or the pie, represents a whole, therefore the slices comprising it should sum up into a significant whole.
Here is an example:

*Q. How many times do you watch TV per week?

It actually makes no sense to represent four TV watching habits as slices of a pie chart, obviously there are many more than the four mentioned in the question. The 'whole' in this case, is meaningless. Now, look at the green and yellow slices? Can you easily tell which one is larger? A bar chart would be a more appropriate display to compare performances of the selected TV watching habits.

What Is The Big Picture?

The other weakness I’ve noticed in SurveyMonkey™ is its lack of ability to 'see' the Big Picture.
Survey data has a huge advantage over other types of data – it is structured.
By 'structured', I mean that we not only know how many people chose a specific answer. The data can also tell how many did not. Furthermore, there are relations between the different questions. For example, the data can tell how many males in their 30s prefer chocolate ice-cream and what they prefer to do in their free time.

There is a lot of uncovered information under the bars and numbers reflecting individual answer choices. To uncover this information you need strong filtering and analysis capabilities. With SurveyMonkey™, we cannot access this hidden gem.

In my next blog post I'll discuss how using online analytical tools will fill in those gaps and complement SurveyMonkey’s great data collection capabilities. I'll demonstrate how working with SurveyMonkey™ data on groketeer can be effortless and streamlined and how to fully understand what the numbers are saying.

Next: Improving Survey Analysis for SurveyMonkey™: Part 2

groketeer lets people upload, analyze and understand survey data and then share their findings with others.
In this video I am showing how to create charts and powerpoint(tm) slides using the tool.